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Record W2069504890 · doi:10.1177/1071791907304285

Falling Over Ourselves to Follow the Leader

2007· article· en· W2069504890 on OpenAlexaff
Igor Kotlyar, Leonard Karakowsky

Bibliographic record

VenueJournal of Leadership & Organizational Studies · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsYork University
Fundersnot available
KeywordsTransformational leadershipPsychologyTransactional leadershipShared leadershipSituational ethicsLeadership styleSocial psychologySituational leadership theoryDysfunctional familyPublic relationsServant leadershipPolitical science

Abstract

fetched live from OpenAlex

Recently, there has been growing interest in more fully examining the situational conditions under which the positive effects of charismatic or transformational leadership are actually achieved. The positive impact of transformational leadership on follower performance has received wide support in the literature. However, much less is known about the impact of transformational leadership on team performance. Although a number of authors have attempted to connect transformational leadership with higher levels of team performance, there has been little effort to delineate the relationship between transformational leadership and teamwork processes or skill sets. This article offers a conceptual examination of the potential link between transformational leadership behavior and the generation of dysfunctional team conflict. Although traditionally praised as a powerful and superior form of leadership style, we suggest that transformational leaders have the potential to unwittingly ignite disproportionately high levels of affective team conflict.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0080.009
Scholarly communication0.0060.004
Open science0.0010.006
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0130.009

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.184
GPT teacher head0.380
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations42
Published2007
Admission routes1
Has abstractyes

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